Building a Smart Shelf Audit and Restocking Bot with UiPath: A Real-World Automation Story

Introduction

Retail and inventory management rely heavily on accurate shelf audits and timely restocking. In large operations, this process can be time-consuming and error-prone when done manually. To solve this problem, I developed a Smart Shelf Audit and Restocking Bot using UiPath — an end-to-end automation that scans shelf data, identifies issues, and sends four daily reports straight to my inbox.

This article walks through how I built this solution using UiPath Studio, Data Service, and Orchestrator — from idea to deployment.

Problem Statement

In a real-world retail environment, stock audits are often:

  • Manual and repetitive
  • Prone to human error
  • Not done frequently enough to catch fast-moving stockouts

These issues can lead to:

  • Lost sales due to out-of-stock items
  • Misplaced products on the wrong shelves
  • Delay in restocking because alerts are not timely

I wanted to automate this process to ensure consistent shelf monitoring and proactive restocking decisions.


:puzzle_piece: Solution Overview

The Smart Shelf Audit and Restocking Bot was designed to:

  1. Pull mock shelf data from UiPath Data Service
  2. Analyze stock levels and detect:
  • Low stock
  • Misplaced items
  • Restocking requirements
  1. Generate four reports:
  • Audit Report
  • Inventory Report
  • Low Stock Products Report
  • Restocking Report
  1. Email these reports to me every morning automatically

This is achieved through UiPath Studio, Excel automation, conditional logic, and integration with Outlook via Orchestrator scheduling.


:building_construction: Architecture Diagram (Optional Visual Aid)

(Let me know if you’d like me to create a diagram — I can generate one for you.)


:gear: Key Components

Here are the main components used in this automation and their purposes:

  • UiPath Studio
    Used to develop the entire automation workflow with drag-and-drop activities.
  • UiPath Data Service
    Acts as a centralized location to store and manage structured mock shelf data.
  • Excel Activities
    Generate and format multiple report files such as Inventory Report, Audit Report, etc.
  • Outlook Activities
    Send the generated reports via email as file attachments each morning.
  • UiPath Orchestrator
    Publishes, deploys, and schedules the automation to run automatically every morning without manual intervention.

:magnifying_glass_tilted_left: Step-by-Step Workflow

:one: Read Shelf Data

Using Data Service Activities, I fetch mock data representing item name, quantity, and location from a pre-defined entity.

:two: Analyze Stock & Shelf Accuracy

In a For Each Row loop, the bot:

  • Flags low stock based on threshold
  • Checks for missing or misplaced items
  • Categorizes products that need restocking

:three: Generate Reports

Each category is written to a separate Excel file using:

  • Write Range
  • Dynamic file naming based on timestamp

:four: Send Daily Email

The bot compiles all four reports and sends an Outlook email using Send Outlook Mail Message with attachments:

  • AuditReport.xlsx
  • InventoryReport.xlsx
  • LowStockProducts.xlsx
  • RestockingReport.xlsx

:date: Deployment with Orchestrator

I published the bot to UiPath Orchestrator, configured a daily morning schedule, and set up robot permissions.

The automation is designed to:

  • Run autonomously at a scheduled time
  • Deliver reports without human involvement

:hammer_and_wrench: While the process runs perfectly when triggered manually, I’m currently troubleshooting a minor issue with scheduled execution via Orchestrator — a common step in refining production-grade bots.


:chart_increasing: Results and Impact

This automation:

  • Eliminates manual shelf checking
  • Ensures daily visibility into stock levels
  • Helps anticipate restocking needs proactively
  • Demonstrates the potential of RPA in retail operations

Future enhancements may include:

  • Real-time shelf monitoring via camera + AI
  • Integration with inventory management systems
  • Automated purchase order generation

:chequered_flag: Conclusion

The Smart Shelf Audit and Restocking Bot is a practical example of how UiPath RPA can streamline retail operations and eliminate repetitive tasks. As I continue refining the solution and working toward UiPath MVP status, I aim to share more learnings, best practices, and components with the community.

If you’re working on something similar or have questions about the process, feel free to connect or drop a message. Let’s build better automations together!

How does it acutally check the stock on the shelves?

Thanks for the great question!

In this version of the project, I’ve used mock data to simulate stock levels on shelves. Since this was developed as a proof of concept (PoC) or demo use case, I used UiPath Data Service to store shelf inventory data, which acts as a placeholder for real-time input.

In a real-world implementation, there are a few ways shelf stock can be checked:

  1. IoT Devices or Smart Cameras: Shelf-mounted sensors or image recognition systems capture stock levels in real time. These can feed data into a database or cloud service that UiPath can access via API.
  2. Barcode/Scanner Input by Staff: Store employees can scan shelf barcodes during routine audits. The scanned data can be pushed into a spreadsheet or a system that the bot can then analyze.
  3. Retail ERP/Inventory System Integration: Many retailers use systems like SAP, Oracle, or in-house databases. The bot can connect to these systems using APIs, SQL queries, or UI automation to pull shelf-level data.

In short, while this automation currently uses mock data, it’s built in a modular way to support integration with real-time stock sources — whether via APIs, IoT, or ERP systems.

Let me know if you’d like to see an example of how to extend this to a real data source!

Most of my career has been spent doing Warehousing and Logistics.

Another avenue to think about is perishable goods or goods with a shelf life and implementing some sort of FIFO into your reporting. oldest product of type on shelf etc

That’s a good. Have you built any project on this?
If not are you interested to work together on this Project?

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